Price Volatility And Hedging Effectiveness Research Of China’s Major Commodity Futures

Under economy globalization and financial markets internationalization, the development of China futures market is getting more and more widespread concern. Especially in the recent 10 years, with the rapid development of China commodity futures market, its trading volume is ranking the first place in the world since 2009, and its role in China’s real economy and the development of mutiple level capital market has become more and more important. Therefore, based on the trading volume, trading amount, time to market, category of commodity and the relastionship with foreign futures, this thesis defines and picks up 8 major commodity futures from more than 40 products in our futures markets, and investiges the characteristics of their price volatility and hedging effectiveness. The main work and fingdings are listed as follows:1. Using GARCH, GJR-GARCH, modified R/S and GPH method, this thesis studies the volatility characteristics of China’s major commodity futures. The results show that returns series of China’s major commodity futures all have the left-skewed and leptokurtic fat tail, which are not subject to the standard normal distribution. Its price volatility has significant volatility clustering and long memory characteristics, but generally don’t have leverage effect.2. Using four kinds of loss function, MCS and dynamic quantile regression testing, we compare the volatility fitting precision and VaR measurement accuracy of GARCH-type models in China’s commodity futures markets. The results show that the volatility fitting precision of the models by skewed student t distribution are not better than the models by normal distribution, but the VaR measurement accuracy are more better. Long memory models don’t significantly improve the volatility fitting precision and VaR measurement accuracy. When the futures market exists leverage effect, GJR-ST, APARCH-ST and FIAPARCH-ST model have an absolute advantage in both conditions.3. Using BEKK-GARCH, PELT method and a staged Copula model, this thesis detect the volatility spillover effect between China’s commodity futures markets and foreign similar futures. The results show that there are bidirectional volatility spillover effect in soybeans, soy meal, sugar, copper and rubber, but the spillover effect from foreign market to domestic market is stronger in agricultural commodity futures. And only have a unidirectional spillover effect from SHFE to LME in zinc futures market. Overall, there is a close association between China’s market and foreign market, the volatility spillover strength and influence from domestic market to foreign market have been strengthened after the financial crisis.4. Using traditional hedging models, static and dynamic Copula method, we study the hedging effectiveness of China’s major commodity futures. The results show that the hedging effectiveness of metal futures (copper and zinc) and energy and chemical futures (rubber and PTA) are significantly higher than agricultural products (soybeans, soy meal and sugar) and the steel (steel rebar). The longer hedging period is, the higher hedge ratios and hedging efficiency. And the hedging effectiveness of different models are different for daily data and weekly data, the traditional hedging models obtain better hedging effectiveness in most cases. While static and dynamic Copula models are better in theory, only show better performance for copper daily data and steel rebar weekly data. In addition, compared with before 2008, the hedging efficiency of China’s major commodity futures has improved to varying degrees, but it is still low relatively, and significantly lower than developed countries.